Gerentes de Recursos Humanos
GerenciaExposición a la IA
- Fuente de datos: BLSPublicado: '26.08
Alto· relativa
BajoCuatro bandas relativasMuy altoValor por grupo ocupacional
Escala, base y fuente
Cuatro bandas relativas (Bajo / Moderado / Alto / Muy alto)
831 ocupaciones detalladas de la tabla de proyecciones de empleo de BLS. El valor se asigna por código de la National Employment Matrix (NEM), de modo que las ocupaciones que comparten un código NEM reciben la misma banda
- Fuente de datos: AnthropicPublicado: '26.03
0.000
0.000Rango de los valores aquí recogidos0.745Escala, base y fuente
Índice de exposición observada, 0–1 tal como se publica
Mapeado sobre tareas de O*NET
- Fuente de datos: ILOPublicado: '25
0.36
0.09Rango de los valores aquí recogidos0.70Valor por grupo ocupacional
Escala, base y fuente
Índice de exposición a la IA generativa, 0–1 tal como se publica
Grupo primario de la CIUO-08 — todas las ocupaciones con ese código reciben este valor
Calculado por este sitio, no publicado por la OIT: de las 1012 ocupaciones que este sitio vincula al conjunto de datos de la OIT, un 60% alcanza o supera este valor.
Qué tipo de cifra publica esta fuente
La categoría de BLS es un rango relativo, no un nivel absoluto, y tampoco es una medición de primera mano: agrupa en cuatro bandas los rangos percentiles de la ocupación en varios estudios publicados. No es una previsión de empleo ni de salarios, no es una probabilidad de adopción y no distingue entre automatización y aumento.
Task-level exposure
Ver 23 tareas ocultas| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Advise managers on organizational policy matters, such as equal employment opportunity and sexual harassment, and recommend needed changes.11-3121 | 0.010050.0 | 0.00000.0 |
Provide terminated employees with outplacement or relocation assistance.11-3121 | 0.010050.0 | —0 |
Analyze statistical data and reports to identify and determine causes of personnel problems and develop recommendations for improvement of organization's personnel policies and practices.11-3121 | 0.00000.0 | 0.0100100.0 |
Values in this tab are predicted labels, not observations. Eloundou et al. (2023) published two rating regimes — human raters and GPT-4 — and the β shown here is derived from the GPT-4 rater basis alone; the same task can take a different value under the other regime. The unit and the meaning differ from the observed shares (%) in the other tabs, so do not place them on the same axis.
| Task | βE1 + 0.5 × E2 |
|---|---|
Conduct exit interviews to identify reasons for employee termination.O*NET Task ID 996 | 1.0 |
Administer compensation, benefits, and performance management systems, and safety and recreation programs.O*NET Task ID 982 | 0.5 |
Identify staff vacancies and recruit, interview, and select applicants.O*NET Task ID 983 | 0.5 |
Allocate human resources, ensuring appropriate matches between personnel.O*NET Task ID 984 | 0.5 |
Provide current and prospective employees with information about policies, job duties, working conditions, wages, opportunities for promotion, and employee benefits.O*NET Task ID 985 | 0.5 |
Perform difficult staffing duties, including dealing with understaffing, refereeing disputes, firing employees, and administering disciplinary procedures.O*NET Task ID 986 | 0.5 |
Advise managers on organizational policy matters, such as equal employment opportunity and sexual harassment, and recommend needed changes.O*NET Task ID 987 | 0.5 |
Analyze and modify compensation and benefits policies to establish competitive programs and ensure compliance with legal requirements.O*NET Task ID 988 | 0.5 |
Serve as a link between management and employees by handling questions, interpreting and administering contracts and helping resolve work-related problems.O*NET Task ID 990 | 0.5 |
Plan, direct, supervise, and coordinate work activities of subordinates and staff relating to employment, compensation, labor relations, and employee relations.O*NET Task ID 991 | 0.5 |
β = E1 + 0.5 × E2 · E1 = tasks where direct LLM access alone cuts time by at least 50%, E2 = tasks where software built on top of an LLM cuts time by at least 50%. Values take only 0 / 0.5 / 1.0.
Data sources & licenses — O*NET®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page